Results 21 to 30 of about 62,654 (265)
Powerset Convolutional Neural Networks
CoRR, 2019 We present a novel class of convolutional neural networks (CNNs) for set functions, i.e., data indexed with the powerset of a finite set. The convolutions are derived as linear, shift-equivariant functions for various notions of shifts on set functions.
Wendler, Chris +2 more
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Convolutional Neural Networks: A Survey
Computers, 2023 Artificial intelligence (AI) has become a cornerstone of modern technology, revolutionizing industries from healthcare to finance. Convolutional neural networks (CNNs) are a subset of AI that have emerged as a powerful tool for various tasks including image recognition, speech recognition, natural language processing (NLP), and even in the field of ...
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Canonical convolutional neural networks
2022 International Joint Conference on Neural Networks (IJCNN), 2022 We introduce canonical weight normalization for convolutional neural networks. Inspired by the canonical tensor decomposition, we express the weight tensors in so-called canonical networks as scaled sums of outer vector products. In particular, we train network weights in the decomposed form, where scale weights are optimized separately for each mode ...
Lokesh Veeramacheneni +3 more
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Research on wear of Ni-Cr alloy milling based on residual network
Advances in Mechanical Engineering, 2022 With the development of the manufacturing industry and information technology, the quality requirements of products are getting higher and higher. A cutting tool is one of the important factors affecting product quality, so it is of great significance to
Shengming Cheng +3 more
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Application of deep learning in recognition of accrued earnings management
Heliyon, 2023 We choose the sample data in Chinese capital market to compare the measurement effect of earnings management with Deep Belief Network, Deep Convolution Generative Adversarial Network, Generalized Regression Neural Network and modified Jones model by ...
Jia Li, Zhoutianyang Sun
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U-Net Pulmonary Nodule Detection Algorithm Based on Multi-scale Feature Structure [PDF]
Jisuanji gongcheng, 2019 Aiming at the defect problem in the low-level characteristics of pulmonary nodules in the process of network transmission,an improved U-Net convolution neural network algorithm based on multi-scale feature structure for pulmonary nodule detection is ...
ZHU Hui,QIN Pinle
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FocusedDropout for Convolutional Neural Network
CoRR, 2021 In convolutional neural network (CNN), dropout cannot work well because dropped information is not entirely obscured in convolutional layers where features are correlated spatially. Except randomly discarding regions or channels, many approaches try to overcome this defect by dropping influential units.
Tianshu Xie +5 more
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Rotational invariant fractional derivative filters for lung tissue classification
IET Image Processing, 2021 A new and powerful rotation invariant fractional derivative convolution neural network model is proposed for the classification of five categories of interstitial lung diseases.
V. N. Sukanya Doddavarapu +2 more
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Convolutional neural networks in APL [PDF]
Proceedings of the 6th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, 2019 This paper shows how a Convolutional Neural Network (CNN) can be implemented in APL. Its first-class array support ideally fits that domain, and the operations of APL facilitate rapid and concise creation of generically reusable building blocks. For our example, only ten blocks are needed, and they can be expressed as ten lines of native APL. All these
Artjoms Sinkarovs +2 more
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Frontiers in Materials, 2021 This paper proposes a novel neural network architecture and its ensembles to predict the critical superconductivity temperature of materials based on their chemical formula.
Dmitry Viatkin +4 more
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